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Known brand, mid-level (3–6 yrs), Bangalore location, and broad requirements increase competition.
Data engineering skills (ETL, Spark, Kafka, AWS) are broadly transferable across industries.
Explicit 3–6 years plus mandatory Java/Python, Spark, cloud, and Kubernetes yields medium strictness.
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Build, optimize, and maintain scalable, high-throughput data ingestion pipelines and backend systems primarily using Java and Python.
Troubleshoot performance bottlenecks related to CPU, memory, and database queries to ensure reliable data flows through ETL pipelines.
Collaborate on system design, conduct code reviews, and manage AWS-based infrastructure, Kubernetes deployments, and CI/CD pipelines with ownership of feature delivery in an Agile/Scrum environment.
3 to 6 years of professional software engineering experience focusing on backend or data-intensive applications.
Strong hands-on proficiency in Java and Python for backend and data engineering.
Experience with building ETL pipelines, Apache Spark, and working knowledge of both SQL (PostgreSQL, MySQL) and NoSQL (DynamoDB, MongoDB, Cassandra) databases.
Proven experience with AWS cloud platform, Kubernetes, Docker, and CI/CD tools (GitLab or Jenkins).
Demonstrated ability to independently own and deliver complex backend/data engineering features from design to production.
Experience solving performance issues in high-volume data environments and optimizing distributed data workflows.
Comfortable working hands-on in a highly collaborative Agile team, participating actively in system design and code quality reviews.